Senior Data Management Analyst

Description

Candidates who live within 50 miles of Boston, MA;
Portsmouth, NH;
Seattle, WA;
Indianapolis, IN;
Columbus, OH; or Plano, TX will follow a hybrid schedule, coming into the office two days per week.

Boston/New York preferred

Join Enterprise Transformation & Solutions (ET&S) as a Sr. Data Management Analyst — an opportunity to be the data advocate for Corporate Procurement, Real Estate, Enterprise Security, and Business Process Solutions. You’ll champion data governance and stewardship, build trusted data products, and partner with business and technical teams to improve data quality, accessibility, and analytics readiness across the enterprise.

This role matters because your work will directly influence Liberty Mutual’s ability to manage enterprise spend, achieve supplier savings targets, and optimize our real estate portfolio. You’ll act as a domain expert, accountable for creating and operationalizing data products, operating with significant autonomy and high visibility to senior leadership. If you want to turn messy data into trusted inputs that drive major financial and operational decisions, this role is built for you.

• Data governance & stewardship
  • Establish, document, and enforce enterprise data governance policies, standards, roles (stewards/owners), and stewardship processes for Corporate Procurement, Real Estate, Enterprise Security, and related functions.
  • Maintain business glossaries, metadata, and lineage documentation to ensure a single source of truth and common business definitions.
• Data quality, lineage & auditing
  • Build and operate automated data quality frameworks (profiling, validation, reconciliation) and lineage tracking to detect, elevate, and remediate data issues.
  • Design audit processes and controls to ensure data integrity and regulatory/compliance readiness.
• Data access, security & controls
  • Implement and manage data access strategies and controls (RBAC, IAM, role‑based access, masking, encryption) in collaboration with IT and security teams.
  • Support data classification, privacy requirements, and best practices for handling sensitive data.
• Data products & architecture support
  • Help design, build, and maintain sustainable data products, pipelines, and architectures (warehouse, lake, Snowflake/Redshift or equivalent) that meet business and analytical needs.
  • Collaborate with engineers to ensure solutions are maintainable, testable, and production‑ready.
• Analytics enablement & tools
  • Provide hands‑on support and best‑practice guidance for analytical tool chains (Power BI, Databricks, Excel, Python) and ensure data is consumable for reporting and advanced analytics.
  • Leverage data cataloging and lineage tools to increase data discoverability and trust.
• Operational automation & continuous improvement
  • Automate recurring data management controls and monitoring to reduce manual effort and improve reliability.
  • Identify process gaps and inefficiencies; propose and lead improvements aligned to business priorities.
• Stakeholder engagement & influence
  • Act as the primary liaison between business leaders (Procurement, Real Estate, Finance, Security) and technical SMEs to translate business needs into governed data solutions.
  • Present findings and recommendations to senior leadership; influence decision‑making through data‑driven insights and trusted relationships.
• Leadership & mentoring
  • Provide technical guidance and mentorship to junior data stewards and analysts.
  • Drive cross‑team collaboration to deliver measurable outcomes and adoption of governance practices.

• Education:
  
  Bachelor’s degree in Business (Finance, Accounting), Computer Science, Information Systems, Data Science, or equivalent experience.
• Experience:
  
  5+ years’ experience in data management, data engineering, data governance, finance or analytics in an enterprise environment.
• Core technical skills:
  • Strong SQL and relational database experience.
  • Hands‑on experience with ETL/ELT tools and modern data platforms (data warehouse and data lake architectures; Snowflake, Redshift, or equivalent).
  • Proficient in Python for data analysis/automation.
  • Practical experience with data catalog / metadata tools and data…